21 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
6 papers
ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care
Zonghai Yao, Talha Chafekar, Junda Wang +5
Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse behavioral, psychosocial, and so…
Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation: A Comparative Study
Won Seok Jang, Sharmin Sultana, Zonghai Yao +4
OpenNotes gives patients access to their EHR notes, but dense medical jargon limits comprehension. We evaluate closed-source and open-source LLMs for extracting and prioritizing th…
Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing
Zonghai Yao, Yi Cao, Zhichao Yang +1
Pretrained language models (PLMs) have motivated research on what kinds of knowledge these models learn. Fill-in-the-blanks problem (e.g., cloze tests) is a natural approach for ga…
Extracting Biomedical Factual Knowledge Using Pretrained Language Model and Electronic Health Record Context
Zonghai Yao, Yi Cao, Zhichao Yang +2
Language Models (LMs) have performed well on biomedical natural language processing applications. In this study, we conducted some experiments to use prompt methods to extract know…
Unsupervised Ensemble Ranking of Terms in Electronic Health Record Notes Based on Their Importance to Patients
Jinying Chen, Hong Yu
Background: Electronic health record (EHR) notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information…
Building an Evaluation Scale using Item Response Theory
John P. Lalor, Hao Wu, Hong Yu
Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption…